Feel-Good Requirements: Neurophysiological and Psychological Design Criteria of Affective Touch for (Assistive) Robots

Previous research has shown the value of the sense of embodiment, i.e., being able to integrate objects into one's bodily self-representation, and its connection to (assistive) robotics. Especially, tactile interfaces seem essential to integrate assistive robots into one's body model. Beyond functional feedback, such as tactile force sensing, the human sense of touch comprises specialized nerves for affective signals, which transmit positive sensations during slow and low-force tactile stimulations. Since these signals are extremely relevant for body experience as well as social and emotional contacts but scarcely considered in recent assistive devices, this review provides a requirement analysis to consider affective touch in engineering design. By analyzing quantitative and qualitative information from engineering, cognitive psychology, and neuroscienctific research, requirements are gathered and structured. The resulting requirements comprise technical data such as desired motion or force/torque patterns and an evaluation of potential stimulation modalities as well as their relations to overall user experience, e.g., pleasantness and realism of the sensations. This review systematically considers the very specific characteristics of affective touch and the corresponding parts of the neural system to define design goals and criteria. Based on the analysis, design recommendations for interfaces mediating affective touch are derived. This includes a consideration of biological principles and human perception thresholds which are complemented by an analysis of technical possibilities. Finally, we outline which psychological factors can be satisfied by the mediation of affective touch to increase acceptance of assistive devices and outline demands for further research and development

Feel-Good Requirements: Neurophysiological and Psychological Design Criteria of Affective Touch for (Assistive) Robots

Previous research has shown the value of the sense of embodiment, i.e., being able to integrate objects into one's bodily self-representation, and its connection to (assistive) robotics. Especially, tactile interfaces seem essential to integrate assistive robots into one's body model. Beyond functional feedback, such as tactile force sensing, the human sense of touch comprises specialized nerves for affective signals, which transmit positive sensations during slow and low-force tactile stimulations. Since these signals are extremely relevant for body experience as well as social and emotional contacts but scarcely considered in recent assistive devices, this review provides a requirement analysis to consider affective touch in engineering design. By analyzing quantitative and qualitative information from engineering, cognitive psychology, and neuroscienctific research, requirements are gathered and structured. The resulting requirements comprise technical data such as desired motion or force/torque patterns and an evaluation of potential stimulation modalities as well as their relations to overall user experience, e.g., pleasantness and realism of the sensations. This review systematically considers the very specific characteristics of affective touch and the corresponding parts of the neural system to define design goals and criteria. Based on the analysis, design recommendations for interfaces mediating affective touch are derived. This includes a consideration of biological principles and human perception thresholds which are complemented by an analysis of technical possibilities. Finally, we outline which psychological factors can be satisfied by the mediation of affective touch to increase acceptance of assistive devices and outline demands for further research and development

Trustworthiness in networks: A simulation approach for approximating local trust and distrust values

International audienceTrust is essential for most social and business networks in the web, and determining local trust values between two unfamiliar users is an important issue. However, many existing approaches to calculating these values have limitations in various constellations or network characteristics. We therefore propose an approach that interprets trust as probability and is able to estimate local trust values on large networks using a Monte Carlo simulation method. The estimation is based on existing indirect trust statements between two unfamiliar users. This approach is then extended to the SimTrust algorithm that incorporates both trust and distrust values. It is implemented and discussed in detail with examples. Our main contribution is a new approach which incorporates all available trust and distrust information in such a way that basic trust properties are satisfied